The recent rapid developments in NLP have witnessed the tremendous success of moving towards unified text models for both understanding and generation tasks across hundreds of languages, evolving into numerous pre-trained models from encoder-only models focusing on text understanding  [1]}, [2]}, to decoder-only models [3]}, [4]} and encoder-decoder models [5]}, [6]}, [7]}, [8]} for both understanding and generation. The pre-training methods in speech have started to show a similar trend towards unified models from the dominant encoder-only models [9]}, [10]}, [11]}, [12]}, [13]} to generative models on cross-modal speech and text data, exemplified by a couple of recent trails such as decoder-only models [14]} and encoder-decoder models [7]}, [16]}, [17]}, [18]}, [19]}, [20]}.
